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Updated: May 1, 2026

Rejection of Fluorescence Background in Resonance and Spontaneous Raman Microspectroscopy
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人工智能和拉曼光谱的可行性,以确定碎肉的真实性

Aleksandar Nedeljkovic1, Aristide Maggiolino2, Gabriele Rocchetti3

  • 1Department of Animal Source Food Technology, Faculty of Agriculture, University of Belgrade, Nemanjina 6, 11080 Belgrade, Serbia.

Foods (Basel, Switzerland)
|September 13, 2025
PubMed
概括

使用机器学习的拉曼光谱学准确识别了碎肉物种. 同质化显著提高了准确性,支持矢量机在复杂混合物中表现最好,用于检测食品欺诈.

关键词:
人工神经网络的人工神经网络随机的森林 随机的森林支持矢量机器 支持矢量机器伪造 伪造 伪造化学测量方法 化学测量方法机器学习是机器学习.快速分析 快速分析

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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...
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